BioDataome: a collection of uniformly preprocessed and automatically annotated datasets for data-driven biology. (2nd March 2018)

• Record Type: Journal Article
• Authors: Lakiotaki, Kleanthi; Vorniotakis, Nikolaos; Tsagris, Michail; Georgakopoulos, Georgios; Tsamardinos, Ioannis
• Is Part Of: Database. Volume 2018(2018)
• Publication Date: 2018-03-02
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/bay011
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: Biotechnology revolution generates a plethora of omics data with an exponential growth pace. Therefore, biological data mining demands automatic, 'high quality' curation efforts to organize biomedical knowledge into online databases. BioDataome is a database of uniformly preprocessed and disease-annotated omics data with the aim to promote and accelerate the reuse of public data. We followed the same preprocessing pipeline for each biological mart (microarray gene expression, RNA-Seq gene expression and DNA methylation) to produce ready for downstream analysis datasets and automatically annotated them with disease-ontology terms. We also designate datasets that share common samples and automatically discover control samples in case-control studies. Currently, BioDataome includes ∼5600 datasets, ∼260 000 samples spanning ∼500 diseases and can be easily used in large-scale massive experiments and meta-analysis. All datasets are publicly available for querying and downloading via BioDataome web application. We demonstrate BioDataome's utility by presenting exploratory data analysis examples. We have also developed BioDataome R package found in: https://github.com/mensxmachina/BioDataome/ . Database URL: http://dataome.mensxmachina.org/